Current methods to detect microbes from a sample usually involve time-consuming steps, such as culturing and/or nucleic acid amplification. For instance, microbial DNA amplification by polymerase chain reaction (PCR), which is used in many assay methods, may take upwards of several hours. Likewise, the culturing of microbes in a sample may take several days or even weeks. The results obtained from such assays are typically non-quantitative. In addition, culturing and nucleic acid amplification techniques are prone to yield false positive as well as false negative results.
The aforementioned challenges in detecting microbes are further amplified when very few target microbes of interest are present within a particular sample. For instance, conventional detection methods may lack the sensitivity required to detect on the order of about 5-10 microbial cells in a sample. Detection is further problematic when non-target microbes are co-present with the target microbes. Such non-target microbes are often termed background flora. Challenges associated with sample analysis also become even more difficult when samples are derived from complex sources, such as, for example, dilute liquid solutions, biological samples and processed food sources (e.g., peanut butter).
The collection of microbial samples from various sources also presents certain challenges, as many conventional collection techniques do not provide a sufficiently sterile environment to avoid introducing microbial contamination. Such standard collection methods may be especially impractical for collecting and preserving samples with very few target microbes of interest.
In recent years, flow cytometry has been used to detect microbes from various samples. However, such methods also have limitations because many samples have natural fluorescence as well as background particles that can reduce the certainty that detected signals represent the microbes of interest. Furthermore, the calibration, standardization, and general operation of flow cytometers to yield consistent results can provide challenges, especially to users with limited expertise in flow cytometry.
In view of the foregoing, there is current need for methods, systems and kits to be used in detection of target microbes in a sample using rapid, quantitative, specific, consistent, and un-complicated protocols. There is a further need that such methods, systems and kits be amenable to samples containing few target microbes of interest and to complicated sample matrices. Various embodiments of the present disclosure utilize flow cytometry methods and systems to address one or more of these unmet needs.